Mastra is an open-source TypeScript framework for building AI agents and AI-powered applications. It bundles agents, workflows, memory, evaluation, and observability into one package that runs inside Next.js and Node.js projects or deploys standalone, giving JavaScript teams a complete alternative to Python-first agent stacks.
What does Mastra include beyond agents?
An agent carries instructions, tools, and a model, then everything around it ships in the same framework: suspendable, resumable agentic workflows, persistent agent memory, retrieval backed by your vector database, plus evaluation and tracing for production monitoring. Tools declare typed input schemas, so arguments validate before execution. The bet is that TypeScript teams should not have to assemble five separate libraries to match what Python frameworks bundle by default.
Mastra or the Vercel AI SDK?
They complement more than compete. The Vercel AI SDK supplies the provider abstraction and streaming interface primitives Mastra builds upon; Mastra adds the framework layer above them: stateful workflows, scheduling, memory, and evaluation. Pick the raw SDK for a chat feature inside an existing app; pick Mastra once agents become the application itself. If you would otherwise reach for LangGraph in Python, Mastra is its closest TypeScript counterpart.
Frequently asked questions
Is Mastra only for Next.js apps?
No. It integrates with React, Node.js, Express, Astro, SvelteKit, and other frameworks, or runs as a standalone HTTP server so any client can call registered agents and workflows as endpoints.
What does Mastra provide that plain libraries do not?
The surrounding product surface: durable suspendable workflows, persistent memory per agent or thread, retrieval, built-in evaluations, and tracing, all sharing one registry. Assembling that from individual libraries is exactly the work Mastra removes.
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